The development of photovoltaic panels has soared in recent years, with a view to making increasing use of renewable energy sources in order to reduce the harmful greenhouse effect caused especially by carbon dioxide emission.
This is the case also for renewable energy sources such as wind-power generators or thermoelectric sources.
These energy sources have the particular feature in which the electrical energy that they provide varies greatly as a function of natural phenomena feeding them. A photovoltaic generator is a generator whose characteristic curve I=f(U) is highly non-linear. Thus, for a same value of illumination, the power delivered will be different depending on the load.
Thus, the efficiency, i.e. the delivered power of a photovoltaic cell, depends not only on its exposure to the sun which varies during the day but also on the concealment of the sun, for example by the shadows thrown by clouds or other weather phenomena.
Besides, when these cells are connected to a load such as a consumer (for example a sensor or else a battery to be recharged), it turns out that the power transferred to the load generally does not correspond to the maximum power that could be delivered by the cell. Similar problems are seen in the case of wind-generated power. As a result, is that efficiency drops not only for example because there is less sunlight but because this efficiency is further reduced by an imposed operating point situated below the potential performance characteristics of the cell.
In order to overcome this drawback and produce energy that is always as close as possible to the optimal operating power point, circuits implementing a method known as the Maximum Power Point Tracking (MPPT) method have been developed since 1968. It consists in providing a better connection between a non-linear source and an arbitrary load.
These circuits are designed to force the generator, such as the photovoltaic cell, to work at its maximum power point, thus giving rise to improved efficiency.
An MPPT controller therefore makes it possible to drive the static converter connecting the load (a battery for example) and the photovoltaic panel so that the load is permanently provided with maximum power.
There is a known method based on a “perturbation and observation” method that is applied when tracking the maximum power point (MPP).
In the case of a photovoltaic application, this is actually an algorithm which, for a fixed voltage U1, will measure the corresponding power P1 delivered by the generator. Then, after a certain period of time, the algorithm dictates a voltage U2=U1+ΔU and also measures the corresponding power P2. Subsequently, a voltage U3=U2+ΔU is dictated if P2 is greater than P1 or, if not, a voltage U3=U2−ΔU.
However, this implies measurements of current and also substantial computation resources, the energy consumption of which is non-negligible. This is why, in a large-sized photovoltaic installation, a sub-group of cells is dedicated exclusively to providing the energy needed to control the MPPT circuit.
However, in electronic micro-systems such as for example autonomous sensors, this approach is not acceptable because the constraints in terms of space requirement and weight are great and it is necessary to have the smallest possible system with increased autonomy.
There also exist known maximum power point tracking circuits that possess an additional driving cell, and this is not always desirable.
There also exist known MPPT circuits without driving cells, based on open-circuit voltage sampling. This sampling is done by disconnecting the photovoltaic panel at fixed frequency from the rest of the circuit to measure the voltage in an open circuit. The system then reconnects the panel to the harvesting circuit which has taken the new optimized parameters into account. However, this results in frequent interruptions of the energy harvesting process, and this is not permissible for electronic micro-systems designed to be autonomous.